Data Loading and Preparation

Loading Data

Data Preparation

Lat : The latitude of the Uber pickup
Lon : The longitude of the Uber pickup
Base : The TLC base company code affiliated with the Uber pickup
The globe is split into an imaginary 360 sections from both top to bottom (north to south) and 180 sections from side to side (west to east). The sections running from top to bottom on a globe are called longitude, and the sections running from side to side on a globe are called latitude.
Latitude is the measurement of distance north or south of the Equator.
Every location on earth has a global address. Because the address is in numbers, people can communicate about location no matter what language they might speak. A global address is given as two numbers called coordinates. The two numbers are a location's latitude number and its longitude number ("Lat/Long").

Analysis of journey by Week-days

seems to have highest sales on Thursday

Analysis by Hour

It peaks during evening time when people are logging off from work

Analysis of Rush of each hour in each month

analysis of which month has max rides

Analysis of Journey of Each Day

Analysis of Total rides month wise

getting Rush in hour

Rush hours are in the morning when people are going to work and afternoon when they coming back from work.

adding hue params

The rush hours are mainly in the middle of the week between 7AM and 7PM when people are going to work and return home. That is the reason we can observe a decrease in latitude on weekend.

Seems like B02617 and B02764 are showing a sharp increase on Summer months while rest of the baslines remain on the same number of journeys most of the time.

2 Cross Analysis

Through our exploration we are going to visualize:

1.Heatmap by Hour and Weekday.

2.Heatmap by Hour and Day.

3.Heatmap by Month and Day.

4.Heatmap by Month and Weekday.

Heatmap by Hour and Weekday.

create pivot_tables

creating heatmap so that it can be easily visualize

Analysing the results

We observe that the number of trips increases each month, we can say that from April to September 2014, Uber was in a continuous improvement process.

Spatial Analysis using heatmap to get a clear cut of Rush on Sunday(Weekend)

Uber pickups by the month in NYC

We can see that the number of Uber pickup has been steadily increasing throughout the first half of 2015 in NYC

Analysing Rush in New york City

Interestingly, after the morning rush, the number of Uber pickups doesn't dip much throughout the rest of the morning and early afternoon. There is significantly more demand in the evening than the daytime. Let's investigate to see if there's a difference in hourly pattern for different days of the week.

Analysing In-Depth Analysis of Rush in New york City Day & hour wise

group the data by Weekday and hour

Like in our previous analysis, we can observe that in the middle of the week the morning rush is basicaly the same while on weekend it drops down because people stay home. On the other hand, there is a slight increase in demand on afternoon and evening because people tend to travel and hangout.